Buckets:
| # Model merge[[peft.utils.merge_utils.prune]] | |
| PEFT provides several internal utilities for [merging LoRA adapters](../developer_guides/model_merging) with the TIES and DARE methods. | |
| - **tensor** (`torch.Tensor`) --The tensor to prune. | |
| - **density** (`float`) --The fraction of values to preserve. Should be in [0,1]. | |
| - **method** (`str`) --The method to use to prune. Should be one of ["magnitude", "random"]. | |
| - **rescale** (`bool`) --Whether to rescale the result to preserve the expected value of the original tensor.`torch.Tensor`The pruned tensor. | |
| Prune the values of task tensors based on the `method`. | |
| - **tensor** (`torch.Tensor`) --The tensor to get the mask from. | |
| - **method** (`str`) --The method to use to get the mask. Should be one of ["total", "frequency"].`torch.Tensor`The majority sign mask. | |
| Get the mask of the majority sign across the task tensors. Task tensors are stacked on dimension 0. | |
| - **task_tensors** (`torch.Tensor`) --The task tensors to merge. | |
| - **majority_sign_mask** (`torch.Tensor`) --The mask of the majority sign across the task tensors.`torch.Tensor`The merged tensor. | |
| Merge the task tensors using disjoint merge. | |
| - **task_tensors(`List[torch.Tensor]`)** --The task tensors to merge. | |
| - **weights** (`torch.Tensor`) --The weights of the task tensors.`torch.Tensor`The merged tensor. | |
| Merge the task tensors using `task arithmetic`. | |
| - **task_tensors(`List[torch.Tensor]`)** --The task tensors to merge. | |
| - **weights** (`torch.Tensor`) --The weights of the task tensors. | |
| - **density** (`float`) --The fraction of values to preserve. Should be in [0,1]. | |
| - **majority_sign_method** (`str`) -- | |
| The method to use to get the majority sign mask. Should be one of ["total", "frequency"].`torch.Tensor`The merged tensor. | |
| Merge the task tensors using `ties`. | |
| - **task_tensors(`List[torch.Tensor]`)** --The task tensors to merge. | |
| - **weights** (`torch.Tensor`) --The weights of the task tensors. | |
| - **density** (`float`) --The fraction of values to preserve. Should be in [0,1].`torch.Tensor`The merged tensor. | |
| Merge the task tensors using `dare linear`. | |
| - **task_tensors(`List[torch.Tensor]`)** --The task tensors to merge. | |
| - **weights** (`torch.Tensor`) --The weights of the task tensors. | |
| - **density** (`float`) --The fraction of values to preserve. Should be in [0,1]. | |
| - **majority_sign_method** (`str`) -- | |
| The method to use to get the majority sign mask. Should be one of ["total", "frequency"].`torch.Tensor`The merged tensor. | |
| Merge the task tensors using `dare ties`. | |
Xet Storage Details
- Size:
- 2.52 kB
- Xet hash:
- 36dc7ac76f6378da9898049b781c6235d7be2137965ad9bab3444bfbcfb29202
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.